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AvrideAvrideAustin, TX

Lead AI Infrastructure Engineer

Lead the ML infrastructure layer with focus on optimizing GPU inference performance for real-time onboard and high-throughput offboard autonomous driving applications. Requires deep experience with PyTorch, C++, GPUs, distributed systems, and performance optimization.

Salary not listed
On-site5+ YOEML Engineering

About the role

What you'll do

  • Take ownership of the GPU inference framework with a focus on performance for both onboard (near real-time) and offboard (high throughput, deterministic) applications.
  • Assume responsibility for broader ML infrastructure across ML pipelines.
  • Collaborate closely with the applied ML team on neural model architectures.

What you'll need

  • Experience with PyTorch.
  • Strong understanding of GPU architecture and operation.
  • Experience diagnosing and resolving performance issues.
  • Strong record building infrastructure, including distributed systems.
  • 5+ years of experience with C++.
  • Programming experience in multi-threaded environments (multiple processes, threads, timers, interrupts).

Skills

PyTorchC++GPUDistributed Systemsmulti-threading

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